The detection of the concentration level of glucose or other analytes in certain individuals may be vitally important to their health. For example, the monitoring of glucose levels is particularly important to individuals with diabetes or pre-diabetes. People with diabetes may need to monitor their glucose levels to determine when medication (e.g., insulin) is needed to reduce their glucose levels or when additional glucose is needed.
Devices have been developed for automated in vivo monitoring of analyte time series characteristics, such as glucose levels, in bodily fluids such as in the blood stream or in interstitial fluid. Some of these analyte level measuring devices are configured so that at least a portion of a sensor of an on-body device is positioned below a skin surface of a user, e.g., in a blood vessel or in the subcutaneous tissue of a user. As used herein, the term analyte monitoring system is used to refer to any type of in vivo monitoring system that uses a sensor disposed with at least a subcutaneous portion to measure and store sensor data representative of analyte concentration levels automatically over time. Analyte monitoring systems include both (1) systems such as continuous glucose monitors (CGMs) which transmit sensor data continuously or at regular time intervals (e.g., once per minute) to a processor/display unit and (2) systems that transfer stored sensor data in one or more batches in response to a prompt or request signal from a processor/display unit (e.g., based on an activation action and/or proximity using, for example, a near field communications protocol).
In some cases, analyte monitoring systems have been found to occasionally provide false readings due to one or more error conditions. In such instances, the analyte monitoring systems maybe described as operating in a fault mode. End of sensor life and early signal attenuation (ESA) are two examples of fault modes where false readings may occur. A decaying sensor signal due to sensor removal, patch adhesive issues, and depleted sensing chemistry are examples of causes of false readings at the end of a sensor's life. Prior art methods of detecting fault modes typically rely on in vivo calibration that compares the sensor's output with one or more in vitro reference glucose readings. Using several in vitro reference glucose readings, both the calibration factor and fault modes such as end of sensor life and ESA can be determined/detected. However, using in vitro reference glucose readings typically requires user interaction, uncomfortable “finger stick” blood samples, a supply of relatively costly test strips, and a meter that can read the test strips. Thus, what is needed are systems, methods and apparatus that do not rely on in vitro reference glucose readings to detect fault modes such as end of sensor life and ESA.